Masterclass Series: Complete Redesign That Actually Works

Sonos replaced its CEO last week. The company faced significant backlash after launching a redesigned app earlier last year that was plagued by bugs, missing features, and connectivity issues, frustrating customers and tarnishing its reputation. This also led to layoffs, poor sales, and a significant drop in stock price.

While I usually don’t comment on companies I’m not involved with, as a long-time Sonos user, I was very frustrated that the alarm feature I had been relying on to wake me up in the morning for well over a decade disappeared overnight. There were other issues, too.

Throughout my career, I have worked on numerous redesign projects. A fiasco like this is totally avoidable. Today, I am sharing a couple of internal blog posts I wrote for my team (when I was Wattpad’s CEO) about this topic. Of course, these are just examples of the general framework I used. In practice, there are many specific details in each redesign that I helped guide the team through, as frameworks like this are like a hammer. Even the best hammer in the world is still just a hammer. The devil is in the details of how you use it.

These internal blog posts are just some of the hammers and drills in my toolbox that I use to help our portfolio CEOs navigate trade-offs and move fast without breaking things.

Happy reading through a sample of my collection of half a million words!

Note: These two posts have been mildly edited to improve readability.

Blog Post #1 – Subject: Feature Backward Compatibility

I have gone through major technology platform redesigns many times in my career. One problem that arises every single time is backward compatibility.

The reason is easy to understand: users can interact with complex products (such as Wattpad) in a million different ways. There is no way the engineering team could anticipate all the permutations.

There are two common ways to solve this problem. First, run an extensive beta program. This is what big companies like Apple and Microsoft do when they update their operating systems. This approach is also a great way to push some of the responsibility to their app developers. Even with virtually unlimited resources, crowdsourcing from app developers is still a far better approach. However, running an extensive beta program takes a lot of time and resources. Most companies can’t afford to do that.

The other approach is to roll out the changes progressively and incrementally. It is very tempting to make all the big changes at once, roll them out in one shot, and roll the dice. However, I am almost certain that it will backfire. Not only is it a frustrating experience for both users and engineers, but it also makes the project schedule much less predictable and, in most cases, causes the project to take much longer than anticipated.

Next year, when we focus on our redesign to reduce tech debt, don’t forget to set aside some time budget for these edge conditions that are so easily overlooked. Also, think about how we can roll out the changes more incrementally to minimize the negative impact on our users.

Blog Post #2 – Subject: The Reversibility and Consequentiality Framework

The other day, I spoke to the CEO of another consumer internet company. In terms of the scale of its user base, this company is much smaller than Wattpad, but we are still talking about millions of users here.

Like us, this company has been around for over a decade. Not surprisingly, technical debt has been an ongoing concern. A few years ago, the team decided to completely redesign its platform from the ground up. The redesign was a multi-year effort, and the team finally pulled back the curtain a year ago. While it is working fine now, this CEO told me that it took a few months before they fixed all the issues and reimplemented all the “missing” features because many of their users were using the product in “interesting” ways that the new version did not support.

These problems are fairly common when redesigning a new system from the ground up. In practice, it is simply impossible to take all the permutations into account, no matter how carefully you plan. However, if we mess things up, our user base is so large that it might negatively impact (or ruin!) 100 million people’s lives in the worst-case scenario.

On the flip side, over-planning could burn through a lot of unnecessary cycles.

One way or another, we should not let these challenges deter us from moving forward or even slow us down because there are many ways to mitigate potential problems. In principle, ensuring that the rollout is reversible and inconsequential is key.

The former is easy to understand: Can we roll back when things go wrong? Do we have a kill switch when updating our mobile apps? These are best practices that we have already been using.

However, at times, these best practices might not be possible. Can we reduce the consequentiality when rolling out? If the iOS app were completely redesigned, could we do it in smaller chunks, parallel-run the new and old versions at the same time, or try the new version on 0.1% of our users first? If not, could we roll out the new app in a small country first?

Again, our objective is not to avoid any problem at all costs. Our objective is to minimize (but not eliminate) the negative impact when things go wrong—not if things go wrong. Although Wattpad going dark for 100 million people for an extended period of time is not acceptable, in the spirit of speed, it is perfectly okay if we have ways to hit reverse or reduce the impact to only a small percentage of our users. These are not rocket science, but they do require a bit more thoughtfulness because our user base is so large that we can’t simply roll the dice.

P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.

Welcoming Albert Chen as a Venture Partner at Two Small Fish Ventures

Today’s blog post is written by Eva and is a reblog of what was originally shared on the Two Small Fish Ventures website.

We are thrilled to announce that Albert Chen is joining Two Small Fish as a Venture Partner!

Albert brings a wealth of experience to our team. Like all our partners at TSF, Albert’s expertise spans the full spectrum—from technical innovation to product development to operational leadership in entrepreneurial startups. His impressive academic background further underscores his exceptional capabilities.

Albert earned his Ph.D. in BioMEMS, Acoustics, and Medical Engineering from the University of Waterloo. He also completed his undergraduate studies in Systems Design Engineering at Waterloo and participated in an international exchange program in Electrical Engineering at National Taiwan University.

Albert’s professional career is equally remarkable. Most notably, he served as the CTO of robotics and edge AI company Forcen. His diverse experience also includes roles at Metergy (smart energy), Excelitas (photonics), and North (smart glass, acquired by Google).

This is just a glimpse of Albert’s impressive journey. Follow him on LinkedIn to learn more about his background and accomplishments.

At Two Small Fish Ventures, we are committed to supporting bold founders shaping the future of technology through our experience. Albert’s extensive academic background, combined with his hands-on leadership and innovation experience, makes him an invaluable addition to our team.

Please join us in welcoming Albert to Two Small Fish!

P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.

Two Small Fish Honoured to Be on the CVCA Top 50 List

Who are the top 50 VCs in Canada? Two Small Fish Ventures is one of them! At Two Small Fish Ventures, we are deeply honoured to be named among Canada’s top 50 venture capital firms in this year’s edition of The 50 — the annual guide produced by the Canadian Venture Capital & Private Equity Association (CVCA) and the Trade Commissioner Service (TCS).

This recognition is not just a badge for us; it’s a reflection of the thriving and globally respected Canadian venture ecosystem we are proud to be part of. We share this honour with an incredible group of firms that are shaping the future of technology, science, and innovation across the country and beyond.

If you are an entrepreneur, this list represents the Canadian VCs you should talk to — firms committed to partnering with visionary founders, pushing boundaries, and building category-defining companies.

We look forward to continuing to back the next generation of transformational founders and are grateful to the CVCA and TCS for this spotlight.

The Full List: Canada’s Top 50 VCs

Here’s the full list of the firms recognized this year (in alphabetical order):

1. Active Impact Investments

2. Amplify Capital

3. Amplitude Ventures

4. AQC Capital

5. BrandProject

6. Brilliant Phoenix

7. Conexus Venture Capital

8. CTI Life Sciences Fund

9. Diagram Ventures

10. Finchley Healthcare Ventures

11. First Ascent Ventures

12. Framework Venture Partners

13. Genesys Capital

14. Good News Ventures

15. Graphite Ventures

16. Greensoil PropTech Ventures

17. GreenSky Ventures

18. iGan Partners

19. Inovia Capital

20. INP Capital

21. InvestEco

22. Luge Capital

23. Lumira Ventures

24. MKB

25. McRock Capital

26. NGIF

27. Panache Ventures

28. Pelorus VC

29. Portage

30. Radical Ventures

31. Raven Indigenous Capital Partners

32. Real Ventures

33. Relay Ventures

34. Renewal Funds

35. Saltagen

36. Sandpiper Ventures

37. Sectoral Asset Management

38. Staircase Ventures

39. SVG Ventures | THRIVE

40. The51 Ventures

41. Two Small Fish Ventures

42. Vanedge Capital

43. Version One Ventures

44. Vistara Growth

45. White Star Capital

46. Whitecap Venture Partners

47. Yaletown Partners

48. Evok Innovations

49. Cycle Capital

50. Boreal Ventures

AI Has Democratized Everything

This is the picture I used to open our 2024 AGM a few months ago. It highlights how drastically the landscape has changed in just the past couple of years. I told a similar story to our LPs during the 2023 AGM, but now, the pace of change has accelerated even further, and the disruption is crystal clear.

The following outlines the reasons behind one of the biggest shifts we identified as part of our Thesis 2.0 two years ago.

Like many VCs, we evaluate pitches from countless companies daily. What we’ve noticed is a significant rise in startups that are nearly identical to one another in the same category. Once, I quipped, “This is the fourth one this week—and it’s only Tuesday!”

The reason for this explosion is simple: the cost of starting a software company has plummeted. What once required $1–2M of funding to hire a small team can now be achieved by two founders (or even a solo founder) with little more than a laptop or two and a $20/month subscription to ChatGPT Pro (or your favourite AI coding assistant).

With these tools, founders can build, test, and iterate at unprecedented speeds. The product build-iterate-test-repeat cycle is insanely short. If each iteration is a “shot on goal,” the $1–2M of the past bought you a few shots within a 12–18 month runway. Today, that $20/month can buy you a shot every few hours.

This dramatic drop in costs, coupled with exponentially faster iteration speeds, has led to a flood of startups entering the market in each category. Competition has never been fiercer. This relentless pace also means faster failures, and the startup graveyard is now overflowing.

For early-stage investors, picking winners from this influx of startups has become significantly harder. In the past, you might have been able to identify the category winner out of 10 similar companies. Now, it feels like mission impossible when there are hundreds—or even thousands—of startups in each category. Many of them are even invisible, flying under the radar for much longer because they don’t need to fundraise.

Of course, there will still be many new billion-dollar companies. In fact, I am convinced that this AI-driven platform shift will produce more billion-dollar winners than ever—across virtually every established category and entirely new ones that don’t yet exist. But by the law of large numbers, spotting them among thousands of startups in each category is harder than ever.

If you’re using the same lens that worked in the past to spot and fund these future tech giants, good luck.

That’s why, for a long time now, we’ve been using a very different lens to identify great opportunities with highly defensible moats to stay ahead of the curve. For example, we’ve been exclusively focused on deep tech—a space where we know we have a clear edge. From technology to product to operations, we have the experience to cover the full spectrum and support founders through the unique challenges of building deep tech startups. So far, this approach has been working really well for us.

I guess we are taking our own advice. As a VC firm, we also need to be constantly improving and striving to be unrecognizable every two years!

There’s no doubt the rules of early-stage VC have shifted. How we access, assess, and assist startups has evolved dramatically. The great AI democratization is affecting all sectors, and venture capital is no exception.

For investors who can adapt, this is a time of unparalleled opportunity—perhaps the greatest era yet in tech investing. The playing field has been levelled, and massive disruption (and therefore opportunities) lies ahead. Incumbents are vulnerable, and new champions will emerge in each category – including VC!

Investing during this platform shift is both exciting and challenging. And I wouldn’t want it any other way, because those who figure it out will be handsomely rewarded.

P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.

Portfolio Highlight: ABR

The next frontier of AI lies at the edge — where data is generated. By moving AI toward the edge, we unlock real-time, efficient, and privacy-focused processing, opening the door to a wave of new opportunities. One of our most recent investments, Applied Brain Research (ABR), is leading this revolution by bringing “cloud-level” AI capabilities to edge devices.

Why is this important? Billions of power-constrained devices require substantial AI processing. Many of these devices operate offline (e.g., drones, medical devices, and industrial equipment), have access only to unreliable, slow, or high-latency networks (e.g., wearables and smart glasses), or must process data streams in real time (e.g., autonomous vehicles). Due to insufficient on-device capability, the only solution today is to send data to the cloud — a suboptimal or outright infeasible approach.

How does ABR solve this? ABR’s groundbreaking technology addresses these challenges by delivering “cloud-sized” high-performance AI on compact, ultra-low-power devices. This shift is transforming industries such as consumer electronics, healthcare, automotive, and a range of industrial applications, where latency, reliability, energy efficiency, and localized intelligence are essential.

What is ABR’s secret sauce? ABR’s unique approach is rooted in computational neuroscience. Co-founded by Dr. Chris Eliasmith, CTO and Head of the University of Waterloo’s Computational Neuroscience Research Group, ABR leverages a brain-inspired invention called the Legendre Memory Unit (LMU), which was invented by Dr. Eliasmith and his team of researchers. LMUs are provably optimal for compressing time-series data—like voice, video, sensor data, and bio-signals—enabling significant reductions in memory usage. Running the

LMU on ABR’s unique processor architecture has created a breakthrough that “kills three birds with one stone” by:

1. Increasing performance,

2. Reducing power consumption by up to 200x, and

3. Cutting costs by 10x.

This is further turbocharged by ABR’s AI toolchain, which enables customers to deploy solutions in weeks instead of months. Time is money, and ABR’s technology allows for advanced on-device functions—like natural language processing—without relying on the cloud. This unlocks entirely new use cases and possibilities.

At the helm of ABR is Kevin Conley, the CEO and a former CTO of SanDisk, alongside Dr. Chris Eliasmith. Together, they bring exceptionally strong leadership across both hardware and software domains—a rare but powerful combination that gives ABR a significant competitive advantage.

ABR’s vision aligns perfectly with our investment thesis and our belief that edge computing and software-hardware convergence represent the next frontier of opportunity in computing. We’re excited to see ABR power billions of devices in the years to come.

P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.